Beat Stress

Problem Addressed

The healthcare wearable devices industry has shown signs of increasing popularity, opening numerous opportunities for different uses of the raised data.  

The current standard methodology for psychological stress detection is the ECG-based Window-derived Heart Rate Variability (W-HRV). However, this technique is not suitable for detecting stress in workers who are exposed to high-pressure environments or extreme conditions in real-time as it requires large time intervals for measurement and produces a large amount of data that needs significant computational power to process. 

This creates an opportunity to develop a more effective method for real time stress detection using wearable devices with the necessary time resolution and computational rapidity. 

Technology

Our solution is Beat Stress, a software based in an innovative algorithm and wearable device capable of detecting stress in 1% of the time required by standard solutions. 

Beat Stress enables the identification of necessary parameters in just one or a few heartbeats (ECG signal) and reduces the volume of data collected and processed. These two features make Beat Stress an ideal technology for integration into a wearable device and real-time usage, in line with the growing trend of healthcare wearables.

Advantages

Fast and accurate: Beat-to-beat stress detection;

Timely stress event prediction - Fast detection of early stress signs in ECG;

Light - Reduces the computational power needed to process the measured data;

Versatile - easy to embed into compact systems, such as wearable, snap-to-skin or under skin devices. 

Possible Applications

• Health and well-being wearable devices; 
• Health assessment of professionals exposed to stressful working environments (firefighters, air traffic controllers, etc…);
• Accident prevention.